About the Role
Our client, a reputable financial institution, is looking for a Compliance Data Analyst to support its Financial Crime Compliance function. This is an exciting opportunity for a data-driven professional to apply advanced analytics and machine learning techniques to enhance financial crime detection, deliver actionable insights, and support the organisation's regulatory compliance and risk management initiatives.
Key Responsibilities
- Analyze large datasets to identify suspicious activities, trends, and emerging compliance risks.
- Design, build, and improve analytical and machine learning solutions to support AML, fraud, sanctions, and compliance monitoring.
- Prepare data-driven insights and reports to support regulatory obligations, audits, and investigations.
- Apply techniques such as logistic regression, random forests, gradient boosting, neural networks, and graph analytics to solve compliance-specific problems.
- Evaluate and monitor the performance of analytical models to ensure accuracy and effectiveness.
- Work closely with Compliance, Risk, and Technology teams to deliver practical, data-led solutions that strengthen risk management.
Requirements
- Degree in Data Science, Statistics, Computer Science, Mathematics, Finance, Economics, or another quantitative discipline.
- 3–7 years of experience in data analytics, data science, or a related field within banking or financial services.
- Experience in financial crime, AML, KYC, fraud, sanctions, or regulatory analytics is an advantage.
- Proficient in SQL and Python or R for data analysis and modelling.
- Good understanding of statistical methods, machine learning techniques, and data visualisation.
